Despite its small sample size, a study in which a patient received closed-loop, deep brain stimulation (DBS) therapy has demonstrated positive clinical outcomes and indicates the potential held by individualised, biomarker-driven neuromodulation for treatment-resistant depression. This is according to a study report authored by Katherine Scangos (University of California, San Francisco, USA) and colleagues, and published in Nature Medicine.
Scangos et al begin their report by noting that DBS is a promising treatment option for neuropsychiatric conditions like major depression and that, due to the complex, underlying neural circuits associated with depressive symptoms, personalised approaches may help to optimise this DBS indication further. They also note that personalisation can be achieved by temporally controlling stimulation—as in closed-loop neuromodulation, whereby a patient’s own physiological activity is used to selectively trigger stimulation only when a certain pathological state is detected.
In addition to this potential for improved success rates in treating depression, they state that closed-loop stimulation also mitigates concerns surrounding neural adaptation, preserves battery life and reduces side-effects. However, they continue, closed-loop therapy requires a symptom-specific biomarker that has not previously been identified in patients with major depression.
In their report, they recount a study involving one 36-year-old female patient with severe, treatment-resistant depression in whom a biomarker of major depressive symptoms was identified during a 10-day period of intracranial corticolimbic circuitry mapping using sEEG electrodes (PMT Corporation). Following this, the researchers successfully implemented the biomarker when unilaterally implanting the US Food and Drug Administration (FDA)-approved RNS system (NeuroPace) in the patient’s right hemisphere, and delivered closed-loop neuromodulation therapy over several months.
Scangos and colleagues report that implementation of closed-loop therapy rapidly improved both symptom severity—which was measured daily with the Six-item Hamilton depression rating scale (HAMD-6) and the visual analogue scale (VAS)—and depression (periodic Montgomery-Åsberg depression rating scale [MADRS]). The patient’s MADRS score decreased from 33 prior to turning on the treatment to 14 at the first during-treatment assessment carried out after 12 days of stimulation, and dropped below 10 (remission) several months later. Similarly, her HAMD-6 and visual analogue scale-depression (VAS-D) scores dropped precipitously the morning after stimulation started, and were lower the week after stimulation was turned on compared to the previous week, the authors add.
To evaluate whether their algorithm triggered stimulus delivery linked to patient symptoms, and not randomly, the researchers used dynamic time warping (DTW) to nonlinearly align daily symptom severity (VAS-D) and biomarker detection count time traces over two months, and calculated their relative post-alignment distance. They found that fluctuation in daily symptoms was significantly associated with fluctuation in the number of device-detected biomarker events—suggesting their biomarker detection algorithm was significantly better at detecting changes in symptom severity as compared to random chance.
“In conclusion, we show the successful development of a personalised biomarker of depression-specific symptoms and implementation of closed-loop therapy for MDD [major depressive disorder],” Scangos et al write. “Success was predicated on a clinical mapping stage before chronic device placement, a strategy that has been utilised in epilepsy to map seizure foci in a personalised manner but has not previously been performed in other neuropsychiatric conditions.
“The new framework presented in this article could advance biomarker-based neural interfaces, and enhance the mechanistic understanding and treatment of a broad range of neuropsychiatric conditions.” Scangos et al
“During this stage, we developed a comprehensive, multimodal framework for selection of sensing and stimulation brain targets. Our approach included personalised stimulus-response mapping, pairing of resting-state signals with clinical symptom measures, and identification of functionally and structurally connected subnetworks across the corticolimbic network.”
The authors note that their research cannot evaluate if this specific biomarker of depression is present in all patients, and go on to acknowledge limitations of the study including its small sample size—which makes it hard to know whether these results will generalise—and the fact clinicians were not always blinded to stimulation location or parameters. However, they add that “the intent of this study was not to address the efficacy of closed-loop neuromodulation for MDD, which would require a double-blind, randomised controlled, adequately powered study”.
“In this study, we established proof-of-concept for a new, powerful treatment approach for neuropsychiatric disorders,” they conclude. “The new framework presented in this article could advance biomarker-based neural interfaces, and enhance the mechanistic understanding and treatment of a broad range of neuropsychiatric conditions.”
